Unraveling the Self-Assembly of Heterocluster Janus Dumbbells into Hybrid Cubosomes with Internal Double-Diamond Structure.

Cubosomes are bicontinuous cubic-phase particles generated by amphiphile self-assembly with bicontinuous cubic phases, which creates an intricate network of interconnected nanochannels that endow these materials with special functions for advanced applications. On the other hand, clusters are an attractive class of molecules that exhibit intriguing functions and properties that differ from those of atoms and nanoparticles. Inspired by lipid self-assembly and attracted to the new functionalities of clusters, we prepared special heterocluster Janus dumbbells (HCJDs) composed of dissimilar nanoclusters: namely, a polyoxometalate and a polyhedral oligomeric silsesquioxane. HCJDs resemble conventional amphiphiles and, as such, they self-assemble in solution into faceted hybrid cubosomes via the transformation of vesicles into spongelike aggregates. Multiple mechanisms that lead to equilibrium, including molecular self-assembly, vesicle accumulation, membrane fusion, inner-structure reorganization, and cubic crystal growth, contributed to the overall process. On the basis of these results, we proposed a strategy for self-assembly-from basic molecular design that goes beyond traditional amphiphiles to the construction of micro- or nanomaterials with hierarchical structures and advanced functions.

Reconstructing porous structures from FIB-SEM image data: Optimizing sampling scheme and image processing.

Nano-porous materials can be imaged spatially by focused ion beam scanning electron microscopy (FIB-SEM). This method generates a stack of SEM images that has to be segmented (or reconstructed) to serve as basis for structural characterization. To this end, we apply two state-of-the-art algorithms. We study the influence of the original image's voxel size on estimates of morphological characteristics and effective permeabilities. Special attention is paid to analyzing anisotropies due to the FIB-SEM typical anisotropic sampling. Quantitative comparison of morphological descriptors and flow properties of reconstructed data is enabled by the use of synthetic FIB-SEM sets for which a ground truth is available. Moreover, in that case, reconstruction parameters can be chosen optimally, too.

Simulation of Leather Visco-Elastic Behavior Based on Collagen Fiber-Bundle Properties and a Meso-Structure Network Model.

Simulation-based prediction of mechanical properties is highly desirable for optimal choice and treatment of leather. Nowadays, this is state-of-the-art for many man-made materials. For the natural material leather, this task is however much more demanding due to the leather's high variability and its extremely intricate structure. Here, essential geometric features of the leather's meso-scale are derived from 3D images obtained by micro-computed tomography and subsumed in a parameterizable structural model. That is, the fiber-bundle structure is modeled. The structure model is combined with bundle properties derived from tensile tests. Then the effective leather visco-elastic properties are simulated numerically in the finite element representation of the bundle structure model with sliding contacts between bundles. The simulation results are validated experimentally for two animal types, several tanning procedures, and varying sample positions within the hide. Finally, a complete workflow for assessing leather quality by multi-scale simulation of elastic and visco-elastic properties is established and validated.